The Dynamics of LOD Sources

Data on the Linked Open Data (LOD) cloud changes frequently. Recent approaches focus on quantifying the changes in the LOD cloud. These metrics are capable to determine changes between two different versions of a dataset, but do not measure the dynamics. In this presentation, we present a method to quantify the changes over time of linked datasets. We define the dynamics of a dataset as the aggregation of absolute, infinitesimal changes, as provided by change metrics. Thus, our method can be parametrized to make use of existing change metrics and incorporates their development over time. As a second contribution, we conduct a systematic investigation of the dynamics of LOD datasets. We apply our analysis on a large-scale LOD dataset that is obtained from the cloud by weekly snapshots over a year. We analyze dynamics at three distinct levels: (i)the data level, based on observations on the set of entities, (ii)the connectivity level, based on observations on the set of interlinks, and (iii)the schema level, based on observations on the set of vocabulary terms that are used in the dataset.